How to use SeerRay-Lab/Xiaomi-OCR-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SeerRay-Lab/Xiaomi-OCR-0") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("SeerRay-Lab/Xiaomi-OCR-0") model = AutoModelForMultimodalLM.from_pretrained("SeerRay-Lab/Xiaomi-OCR-0", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
How to use SeerRay-Lab/Xiaomi-OCR-0 with vLLM:
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SeerRay-Lab/Xiaomi-OCR-0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SeerRay-Lab/Xiaomi-OCR-0", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'
docker model run hf.co/SeerRay-Lab/Xiaomi-OCR-0
How to use SeerRay-Lab/Xiaomi-OCR-0 with SGLang:
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "SeerRay-Lab/Xiaomi-OCR-0" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SeerRay-Lab/Xiaomi-OCR-0", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "SeerRay-Lab/Xiaomi-OCR-0" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SeerRay-Lab/Xiaomi-OCR-0", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'
How to use SeerRay-Lab/Xiaomi-OCR-0 with Docker Model Runner:
恭喜贵团队产出了这个工作！快速浏览了一下技术报告，感觉很多工作做的还是比较扎实的！感谢对PaddleOCR-VL系列、Real5-OmniDocBench的使用，也感谢深度集成PP-DocLayoutV3！让我们一起加速文档智能的发展！
感谢您对Xiaomi-OCR-0的支持和认可！同时非常感谢 PaddleOCR系列优秀工作带来的启发和帮助，让我们受益良多。非常欣赏贵团队一直以来营造的开放、友好、互相促进的社区氛围，让我们携手同行，共同进步！
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